Abstract
We investigate systematically the impact of human intervention in the training of computer players in a strategy board game. In that game, computer players utilise reinforcement learning with neural networks for evolving their playing strategies and demonstrate a slow learning speed. Human intervention can significantly enhance learning performance, but carrying it out systematically seems to be more of a problem of an integrated game development environment as opposed to automatic evolutionary learning.
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Kalles, D. (2007). Measuring Expert Impact on Learning how to Play a Board Game. In: Boukis, C., Pnevmatikakis, A., Polymenakos, L. (eds) Artificial Intelligence and Innovations 2007: from Theory to Applications. AIAI 2007. IFIP The International Federation for Information Processing, vol 247. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-74161-1_12
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DOI: https://doi.org/10.1007/978-0-387-74161-1_12
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